What if a large class of algorithms used today—from the algorithms that help us avoid traffic to the algorithms that identify new drug molecules—worked exponentially faster?
Computer scientists at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a completely new kind of algorithm, one that exponentially speeds up computation by dramatically reducing the number of parallel steps required to reach a solution.
The researchers will present their novel approach at two upcoming conferences: the ACM Symposium on Theory of Computing (STOC), June 25–29 and International Conference on Machine Learning (ICML), July 10 −15.
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